Due to cognitive and socio-emotional decline and mental diseases, senior citizens,
especially people with dementia (PwD), struggle to interact smoothly with their caregivers …

Emotion embedding space learned from references is a straight-forward approach for
emotion transfer in encoder-decoder structured emotional text to speech (TTS) systems …

In this paper, we propose an adversarial network implementation for speech emotion
conversion as a data augmentation method, validated by a multi-class speech affect …

In this paper, we investigate the simultaneous modeling of multiple emotions in DNN-based
expressive speech synthesis, and how to represent the emotional labels, such as emotional …

Abstract Speech Emotion Recognition (SER) is a challengeable task to improve human–
computer interaction. Speech data have different representations, and choosing the …

In this article, we address to what extent the proverb “the sound makes the music” also
applies to human-robot interaction, and whether robots could profit from using speech …

Text-to-speech (TTS), also known as speech synthesis, is a prominent research area that
aims to generate natural-sounding human speech from text. Recently, with the increasing …

Generating versatile and appropriate synthetic speech requires control over the output
expression separate from the spoken text. Important non-textual speech variation is seldom …

In this paper, an end-to-end neural embedding system based on triplet loss and residual
learning has been proposed for speech emotion recognition. The proposed system learns …

The text to speech technology has achieved significant progress during the past decade and
is an active area of research and development in providing different human–computer …